Over at The Molecular Ecologist, I discuss a new paper that exemplifies how we’re going to be studying the genetics of adaptation in the age of high-throughput DNA sequencing—even if it doesn’t quite live up to that promise. It’s a study of adaptation in Atlantic salmon, whose lifestyle makes them uniquely suitable for a particuar sampling design:

Salmon hatch in freshwater rivers, and spend at least their first year in that environment before swimming downstream to the ocean, where they develop into reproductively mature adults. When they’re ready to mate, they migrate back from the ocean, up the river where they hatched to spawn at the site of their birth. Those major migrations and the transitions between freshwater and salt-water are likely to be major selective events for salmon, and they offer convenient times to catch and study salmon from roughly the same age-cohort: when they migrate downstream to the ocean, and when they return to their birth-river.

By taking genetic samples of juvenile salmon on their way out to sea, and then adults on swimming upstream to breed, you can test for genetic changes—adaptation—that has occurred over the course of the fishes’ life in the ocean. And that’s exactly what the authors of this paper did—go read the whole post to find out how it worked.

Over at The Molecular Ecologist I’m discussing a new paper in the journal Genetics, which demonstrates that selection acts more strongly on genes that affect multiple traits:

Genes that have roles in multiple traits—pleiotropic genes—have long been thought to be under stronger selection as a result of those multiple functions. The basic logic is that, when a gene produces a protein that has a lot of different functional roles, there are more functions that will be disrupted by changes to that protein. Which would be more inconvenient: if your smartphone suddenly needed a new type of power connector, or if every electrical outlet in your house suddenly accepted only plugs with four prongs?

A team at the University of Queensland tested this idea using a lot of fruit flies and some cleverly applied gene expression resources. To find out how it all worked, go read the whole post, and check out the original paper.◼

I’ve actually done an entirely open review [for Faculty of 1000] and I found the whole experience rather jarring; I wouldn’t have done it if I didn’t already like the software in question, and I think that could be unethical. Scott’s a nice guy and a good scientist; I’m not certain I would have been viewed very favourably being one of the first people to criticise the work of another in the open, despite the fact I think such a system has a number of benefits.

I do think reviewers should be disclosed on publication in order to get credit for their job, but also to take responsibility of it. In general, I also think signing makes the process more transparent and helps engage in a constructive conversation.

There are some excellent points made on both sides, and I recommend reading the whole compilation of views for and against anonymity.◼

Over at The Molecular Ecologist, John Stanton Geddes continues his interview series with quantitative geneticist Charles Goodnight, whose work covers everything from multi-level perspectives on natural selection to the the causal linkage between directly measurable trait variation and interactions between individual genes. Here’s a sample of what Goodnight has to say about the group selection versus kin selection debate (which I’ve discussed here before):

Why the controversy continues today is not so clear. It is interesting that it is mostly very one sided. Those who champion group selection tend to understand kin selection, and dismiss it because it is not useful to them. Those who tend to champion kin selection tend to not understand group selection and dismiss it because it is a priori wrong.

The interview also covers Goodnight’s thoughts about how molecular genetics has changed the field since his days in graduate school, his experience starting up the blog Evolution in Structured Populations and his estimation of the probability of extraterrestrial invasion—I recommend reading the whole thing.◼

This week at The Molecular Ecologist, I discuss some emerging initiatives to collect biodiversity data with a little help from the entire Internet:

… the websites iSpot and eBird ask volunteers to record their natural history observations directly, creating crowd-sourced records of species occurrences. (iSpot covers everything from amphibians to fungi, while eBird is specialized exactly as you would expect from the name.) Both of these sites provide educational resources in concert with their data-collection missions; iSpot through user-generated quizzes, eBird by helping bird-watchers find new species in their own neighborhoods. And both of them make their datasets public.

Have you ever worked with crowd-sourced data like this? Go read the whole thing, and tell us about your experience in the comments.◼

João Barroso-Batista and colleagues at the Instituto Gulbenkian de Ciência and Instituto de Tecnologia Química e Biológica in Portugal first treated mice with streptomycin to clear their guts of bacteria, then fed them cultures of Escherichia coli that were genetically uniform—except that half the E. coli cells in the culture had been engineered to produce a blue fluorescent protein, and half had been engineered to produce a yellow fluorescent protein. … If a single mutation made that one cell so successful that its descendants entirely dominated the gut, the authors would be able to tell—by checking the color of the host mouse’s poop.

To find out what the study’s authors learned by sequencing the bacterial genomes in that colored mouse poop, go read the whole thing.◼

One of the most popular items at The Molecular Ecologist isn’t a blog post—it’s Travis Glenn’s “Field Guide” to the capabilities and costs of the many next-generation sequencing technologies currently available. Today we’re pleased to release the 2014 update to the Guide, this time with some new personal insight from Travis in the form of both an introductory blog post and a new table rating the overall quality of each technology:

Overall, if you are in the market for a next generation DNA sequencer in early 2014, the data indicate one clear inexorable trend – think Illumina. For fans of the Brady Bunch – Illumina, Illumina, Illumina! For fans of Star Trek – Prepare to be assimilated by one of Illumina’s Borg-like cubes. For fans of Henry Ford – You can have any NSG instrument you want, so long as it’s an Illumina.

At The Molecular Ecologist today, I highlight a couple of recent literature reviews that seek to understand how natural populations are structured by the limitations of distance, and by local adaptation:

Taken together, these two papers are a nice compilation of a very large literature. If nothing else, they demonstrate that we’re well past the point of asking whether environmental isolation happens at all—in fact, it looks to be quite common—and we’re ready to start digging into the details of when and why it develops.

To see what broad patterns two different groups of authors were able to extract from their surveys of many population genetic studies, go read the whole thing.◼

The probable selective impact of Joshua tree’s pollinators is obvious—it easily catches in the sieve of our attention and our desire to work with interesting critters. But I think it’s also fair to ask how much an interaction as specialized as the Joshua tree pollination mutualism actually tells us about the evolution of much more common, much less finely co-adapted relationships.

Do you ever worry that your study system limits what you can, well, study? Go read the whole thing, and tell us in the comments there.◼